MMN can be used to track recovery from the vegetative state in the post-acute phase after severe brain injury. In addition, MMN can be used to predict the ability to recover from the vegetative state.

Almost two-thirds of the patients reached full consciousness. LOC at admission, aetiology and interval since injury were found to be significant prognostic factors. Traumatic patients had a much better outcome than non-traumatic patients. A comparison with earlier outcome studies showed a more favourable outcome than expected. It is argued that a multi-centre study is needed to confirm possible effects of EINP.

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For some patients, coma is followed by a state of unresponsiveness, while other patients develop signs of awareness. In practice, detecting signs of awareness may be hindered by possible impairments in the patient's motoric, sensory, or cognitive abilities, resulting in a substantial proportion of misdiagnosed disorders of consciousness. Task-free paradigms that are independent of the patient's sensorimotor and neurocognitive abilities may offer a solution to this challenge. A limitation of previous research is that the large majority of studies on the pathophysiological processes underlying disorders of consciousness have been conducted using cross-sectional designs. Here, we present a study in which we acquired a total of 74 longitudinal task-free EEG measurements from 16 patients (aged 6–22 years, 12 male) suffering from severe acquired brain injury, and an additional 16 age- and education-matched control participants. We examined changes in amplitude and connectivity metrics of oscillatory brain activity within patients across their recovery. Moreover, we applied multi-class linear discriminant analysis to assess the potential diagnostic and prognostic utility of amplitude and connectivity metrics at the individual-patient level. We found that over the course of their recovery, patients exhibited nonlinear frequency band-specific changes in spectral amplitude and connectivity metrics, changes that aligned well with the metrics' frequency band-specific diagnostic value. Strikingly, connectivity during a single task-free EEG measurement predicted the level of patient recovery approximately 3 months later with 75% accuracy. Our findings show that spectral amplitude and connectivity track patient recovery in a longitudinal fashion, and these metrics are robust pathophysiological markers that can be used for the automated diagnosis and prognosis of disorders of consciousness. These metrics can be acquired inexpensively at bedside, and are fully independent of the patient's neurocognitive abilities. Lastly, our findings tentatively suggest that the relative preservation of thalamo-cortico-thalamic interactions may predict the later reemergence of awareness, and could thus shed new light on the pathophysiological processes that underlie disorders of consciousness.

AIMS: To explore the course of recovery of consciousness and factors predicting the outcome of severe brain injury with a prolonged period of unconsciousness in children and young adults receiving a specialized rehabilitation treatment, the Early Intensive Neurorehabilitation Programme (EINP). METHODS: A cohort of forty-four patients aged 1.6-25.5 years (M = 16.0) with traumatic acquired brain injury (TBI) or nontraumatic acquired brain injury (nTBI) were examined using the Western Neuro Sensory Stimulation Profile every two weeks, from the application for EINP until discharge. The level of consciousness was assessed with the Post-Acute Level of Consciousness Scale, and the level of disability was determined by the Disability Rating Scale. Long-term level of disability of all TBI patients (N = 32) was assessed between 2.0 and 4.4 years after discharge from EINP. RESULTS: Two-thirds of all patients recovered to consciousness. Three recovery patterns were identified: remaining in a vegetative state (VS), slow recovery of consciousness, and fast recovery of consciousness. In the long-term, 11 of the TBI patients were severely disabled, 13 were moderately disabled, and 4 were mildly disabled. All TBI patients who were in VS at discharge either had deceased, or recovered to a very severely disabled state. CONCLUSIONS: Three recovery patterns identified in an early stage after starting EINP made it possible to predict long-term level of disability.